# -*- coding: utf-8 -*-

from datetime import timedelta
from utils.operators.spark_submit import SparkSubmitOperator
jms_ods__metadata_sync = SparkSubmitOperator(
    task_id='jms_ods__metadata_sync',
    email=['zhangqinglin@jtexpress.com','yl_bigdata@yl-scm.com'],
    conn_id='spark_route',
    name='jms_ods__metadata_sync_{{ execution_date | date_add(1) | cst_ds }}',
    # sla=timedelta(hours=7),
    driver_memory='30G',
    executor_memory='20G',
    executor_cores=6,
    num_executors=50,
    pool_slots=3,
    conf={'spark.dynamicAllocation.enabled': 'true',  # 动态资源开启
          'spark.shuffle.service.enabled': 'true',  # 动态资源 Shuffle 服务开启
          'spark.dynamicAllocation.maxExecutors': 50,  # 动态资源最大扩容 Executor 数
          'spark.dynamicAllocation.cachedExecutorIdleTimeout': 60,  # 动态资源自动释放闲置 Executor 的超时时间(s)
          'spark.sql.sources.partitionOverwriteMode': 'dynamic',  # 允许删改已存在的分区
          'spark.executor.memoryOverhead': '6G',  # 堆外内存
          'spark.sql.shuffle.partitions': 800
          },
    # jars='hdfs:///user/spark/work/dm/hejian/dm__dm_waybill_prescription_reach_details/common-1.0-SNAPSHOT.jar',  # 依赖 jar 包
    jars='hdfs:///scheduler/jms/spark/zql/metadata_sync/common-1.0-SNAPSHOT.jar',
    # 依赖 jar 包
    java_class='com.yunlu.bigdata.jobs.GetHiveMetaData',  # spark 主类
    # application='hdfs:///user/spark/work/dm/hejian/dm__dm_waybill_prescription_reach_details/original-jobs-1.0-SNAPSHOT.jar',  # spark jar 包
    application='hdfs:///scheduler/jms/spark/zql/metadata_sync/bigdata-data-sync-1.0-jar-with-dependencies.jar',
    # spark jar 包
    application_args=['jms_ods'],
    execution_timeout=timedelta(hours=1),
)